Triple
T28434290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Submarine Voyage (Disneyland attraction) |
E715218
|
entity |
| Predicate | vehicleCount |
P22510
|
FINISHED |
| Object | 8 submarines |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 8 submarines | Statement: [Submarine Voyage (Disneyland attraction), vehicleCount, 8 submarines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleCount Context triple: [Submarine Voyage (Disneyland attraction), vehicleCount, 8 submarines]
-
A.
numberOfVehicles
chosen
Indicates the total count of vehicles associated with a given entity or context.
-
B.
numberOfCarsPerUnit
Indicates the quantity of cars associated with each single unit of a specified measure (such as time, distance, or entity).
-
C.
numberOfPassengerCars
Indicates the total count of passenger cars associated with or contained in a given entity or context.
-
D.
droveCarNumber
Indicates that a person operated or was driving a specific car identified by its number.
-
E.
quantityPerCar
Indicates the amount or number of a specified item associated with each individual car.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69efd6b253888190b3c7222ed6a403a8 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f64e37f7fc819083809149b6661e3c |
completed | May 2, 2026, 7:19 p.m. |
| PD | Predicate disambiguation | batch_69f64caede108190a35cc7cbfead866f |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 1:41 a.m.